Tag: enterpriseai
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Enterprise harness smack-talk
One enterprise harness maker says the competing enterprises harness makers either suck or are non-existent. When you go to San Francisco and talk to them, their basic vibe is ‘we don’t have to solve your problem today because tomorrow you’re going to go away and all your problems are going to be solved,’” Karp charged.…
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That means each employee’s AI spending cap is ~11% of that median compensation package. Last year, there were a few anecdotes about high growth tech companies spending $100,000/year per head on tokens. That seems like it’s coming to end.a 🔗 Uber Caps Usage of AI Tools Like Claude Code to Manage Costs
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🤖 Valiantys-Glean Partnership Bets That Cross-Platform Knowledge Graphs and Behavioral KPIs Are What Move Enterprise AI Past Pilots
Original: Enterprise AI is still stuck at experimentation – Valiantys and Glean think they know why by diginomica. Summarized by AI on June 3, 2026. Most enterprise AI pilots stall, and the diagnosis from Nathan Chantrenne, Chief AI Officer at Valiantys, is that the field measures the wrong things and fragments its tooling. The dominant…
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50%+ failure is normal
Analyst firm Gartner thinks at least half of all generative AI projects “will overrun their budgeted costs due to poor architectural choices and lack of operational know-how,” and most organizations that try to build custom models “will abandon their efforts due to costs, complexity and technical debt in their deployments.” Yes, and this matches decades…
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Enterprise AI Slop
People are using AI to generate too much work because they think they know what they’re doing: A growing body of work calls this output-competence decoupling. In any previous era, the quality of a piece of work was a more or less reliable signal of the competence of the person who produced it. A novice…
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The users have plenty of feature ideas
AI allows people who aren’t software engineers to build meaningful software. Those of us who are software engineers at companies should stop building features and focus instead on building systems that allow people on the sales team, the factory shop floor, etc. etc. etc. to ship safely. 🔗 notes from o11ycon 2026
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Buy your platform, AI edition
Building an internal agentic AI platform in banking or insurance demands a multi-year orchestration engineering commitment with a regulatory surface area that most organizations underestimate. [Bryan Ross] Tinkers and opexmaxxers take in huge risks when they decide to build their own platforms. And it usually fails, for at least seven reasons. 🔗 The hidden cost…
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Bad advice from Wall Street on enterprise AI.
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Where are the enterprise AI apps? Part n + 1
Outside of programming, there’s still a dearth of enterprise AI apps, it seems. Palo Alto’s CEO: “Consumers are far outstripping enterprise for the moment, but we expect enterprise will surely and slowly get on that bandwagon,” he said on the company’s Q2 earnings call. … “Right now … tell me how many enterprise AI apps…
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Your Boss Doesn’t Know What to Do With AI Enterprise AI Has a Product-Market Fit Problem. Enterprise AI isn’t stalled because the models are weak. It’s stalled because we haven’t discovered product-market fit inside the enterprise yet. You don’t find real AI value by theorizing in workshops. You find it by running experiments for months…
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Lots of yes-but’ing here, inc. this gem for y’all security folk: Wall Street doesn’t understand the reluctance of enterprise CIOs to trust startups with mission-critical data or value the expertise needed to run SaaS reliably at scale as much as the shiny new thing. 🔗 A day of reckoning for the AI boom
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Day 2 AI looms
Achieving enterprise AI ROI still tough: According to a recent Gartner poll, over half (53%) of participants were exploring Agentic AI, whereas 25% were piloting it and only 6% had reached production mode. The high exploration and pilot percentages suggest strong interest and perceived potential in Agentic AI. However, ==the low production percentage implies barriers…
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Amazon’s enterprise AI strategy, explained by Neil Ward-Dutton
Neil Ward-Dutton, an IDC analyst focused on AI, automation, data and analytics, said three announcements on the first day of the conference were of note. “AWS AI Factories is one,” he said. “These are AWS AI infrastructure and software stacks, built and managed by AWS, but deployed in customers’ own datacentres. “These are, at least…
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You need a proxy for enterprise AI Google Cloud suggests using a centralized proxy to mediate all communication between clients and remote MCP servers. This proxy enforces access control, audit logging, secret policies, and secure transport, helping reduce the attack surface by having one enforced point rather than many decentralized servers. In addition, Google emphasizes…
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Anthropic Economic Index report: Uneven geographic and enterprise AI adoption – 🤖: “Enterprise deployment via Anthropic’s API exposes a different facet: businesses adopt AI programmatically to automate. 77% of API usage is automation-dominant, particularly in coding, debugging, office administration, and recruitment. Surprisingly, firms are not especially price-sensitive; higher-cost tasks see higher adoption if they deliver…
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In 2026, I’d like to see a lot more coverage about the actual enterprise AI apps people are building and running. // Agents show promise, but widespread usage in the enterprise remains elusive
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Agentic Design Patterns, book draft –


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